Speed Control of Separately Excited DC Motor Using Neuro Fuzzy Technique PDF Download

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Languages : en
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This paper uses NEURO FUZZY TECHNIQUE in estimating speed and controlling it for a separately excited DC motor. The rotor speed of the dc motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed of saperately excited DC Motor, especially when the motor and load parameters are unknown. Such a neuro fuzzy control scheme consists of two parts. One is the neural identifier which is used to estimate the motor speed error (state error or state error derivative). The second is the fuzzy logic controller which is used to generate a control signal for a chopper & speed control of separately excited DC Motor. The purpose of this technique is to achieve accurate trajectory control of the speed. Such a control scheme consists of two parts. One is the neural identifier which is used to estimate the motor speed. The other is the neural fuzzy logic controller which is used to generate the control signal (fuzzy output).

Author: A.F.M. Sajidul Qadir
Publisher: Lulu.com
ISBN: 1304227650
Category : Technology & Engineering
Languages : en
Pages : 135

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In this book, Mathematical Modelling of a reference SEDM has been done & Transfer Function has been derived with simulated result. Later Parameter Identification has been carried out to find the suitable design criteria for testing different controllers (P, PI, PD, PID controllers) with the machine. As it turned out to be a stable system (as per Routh-Hurwitz Stability Criterion), different controllers has been used to evaluate the Step response of Open loop & Closed loop system with simulated result. Controller tuning has been done to find the best result for controlling speed of SEDM. Settling time, % Overshoot, Steady-State error & Rise time has been calculated for all the controllers. Later active RC realization of the best fitted controller has been done using Ideal PID Control Algorithm.

Author: Beng Kiat Chan
Publisher:
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Category : Electric motors, Direct current
Languages : en
Pages :

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Author: Chin-teng Lin
Publisher: World Scientific Publishing Company
ISBN: 9813104708
Category : Technology & Engineering
Languages : en
Pages : 152

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A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.

Author: Sundarapandian Vaidyanathan
Publisher: Academic Press
ISBN: 0128175834
Category : Technology & Engineering
Languages : en
Pages : 542

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Backstepping Control of Nonlinear Dynamical Systems addresses both the fundamentals of backstepping control and advances in the field. The latest techniques explored include ‘active backstepping control’, ‘adaptive backstepping control’, ‘fuzzy backstepping control’ and ‘adaptive fuzzy backstepping control’. The reference book provides numerous simulations using MATLAB and circuit design. These illustrate the main results of theory and applications of backstepping control of nonlinear control systems. Backstepping control encompasses varied aspects of mechanical engineering and has many different applications within the field. For example, the book covers aspects related to robot manipulators, aircraft flight control systems, power systems, mechanical systems, biological systems and chaotic systems. This multifaceted view of subject areas means that this useful reference resource will be ideal for a large cross section of the mechanical engineering community. Details the real-world applications of backstepping control Gives an up-to-date insight into the theory, uses and application of backstepping control Bridges the gaps for different fields of engineering, including mechanical engineering, aeronautical engineering, electrical engineering, communications engineering, robotics and biomedical instrumentation

Author: Mustefa Jibril
Publisher: GRIN Verlag
ISBN: 3346164152
Category : Computers
Languages : en
Pages : 6

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Academic Paper from the year 2020 in the subject Computer Science - Miscellaneous, , language: English, abstract: The main target of this paper is to control the speed of DC motor by comparing the actual and the desired speed set point. The DC motor is designed using Fuzzy logic and MPC controllers. The comparison is made between the proposed controllers for the control target speed of the DC motor using square and white noise desired input signals with the help of Matlab/Simulink software. It has been realized that the design based on the fuzzy logic controller track the set pointwith the best steady state and transient system behavior than the design with MPC controller. Finally, the comparative simulation result prove the effectiveness of the DC motor with fuzzy logic controller.

Author: Gautam Das
Publisher: Springer
ISBN: 3540305610
Category : Computers
Languages : en
Pages : 438

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The 7th International Conference on Information Technology (CIT 2004) was held in Hyderabad, India, during December 20–23, 2004. The CIT 2004 was a forum where researchers from various areas of information technology and its applications could stimulate and exchange ideas on technological advancements. CIT, organizedby the Orissa InformationTechnologySociety (OITS), has emerged as one of the major international conferences in India and is fast becoming the premier forum for the presentation of the latest research and development in the critical area of information technology. The last six conferences attracted reputed researchers from around the world, and CIT 2004 took this trend forward. This conference focused on the latest research ?ndings on all topics in the area of information technology. Although the natural focus was on computer science issues, research results contributed from management, business and other disciplines formed an integral part. We received more than 200 papers from over 27 countries in the areas of com- tational intelligence, neural networks, mobile and adhoc networks, security, databases, softwareengineering,signal andimageprocessing,andInternetandWWW-basedc- puting. The programme committee, consisting of eminent researchers, academicians and practitioners, ?nally selected 43 full papers on the basis of reviewer grades. This proceedings contains the research papers selected for presentation at the c- ference and this is the ?rst time that the proceedingshave been published in the Lecture Notes in Computer Science (LNCS) series. The poster papers are being printed as a separate conference proceedings.

Author: Ying Bai
Publisher: Springer Science & Business Media
ISBN: 1846284694
Category : Technology & Engineering
Languages : en
Pages : 342

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This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers’ tuning processes and enhance the performance of their control systems. It further contains application examples.

Author: Khairul Afiq Zakaria
Publisher:
ISBN:
Category : Fuzzy logic
Languages : en
Pages : 61

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Book Description
The automatic control has played a vital role in the advance of engineering and science. Nowadays in industries, the control of direct current (DC) motor is a common practice thus the implementation of DC motor of controller speed is important. The main purpose of motor speed control is to keep the rotation of the motor at the present speed and to drive a system at the demand speed. The DC Series Wound Motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. The main purpose of this project is to control speed of DC Series Wound Motor using four controllers which are PID, PI, P, and Fuzzy Logic Controller (FLC). Initially all the controllers are developed by using MATLAB simulink model. In this project, PID, PI, and P controller are developed and tuned in order to get faster step response and the Fuzzy Logic Controller (FLC) is design based on the membership function and the rule base. The expectation of this project is the Fuzzy Logic Controller will get the best performance compared to other controllers in terms of settling time (Ts), rise time (Tr), peak time (Tp), and percent overshoot (%OS). Finally a GUI of these controllers are developed which allow the users to select any controller and change its parameters according to the different conditions under loaded and unloaded scenarios.

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Category :
Languages : en
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This paper uses Artificial Neural Networks (ANNs) in estimating speed and controlling it for a separately excited DC motor. The rotor speed of the dc motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed, especially when the motor and load parameters are unknown. Such a neural control scheme consists of two parts. One is the neural identifier which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neural networks are trained by Levenberg-Marquardt back-propagation algorithm. ANNs used in this are the standard three layers feedforward neural network with sigmoid activation functions in the input and hidden layers while linear activation function is employed for the output layer. The conventional constant gain feedback controller fails to maintain the performance of the system at acceptable levels under unknown dynamics in load torque. On the other hand, ANNs act as an effective tool to implement the model and adaptive control in a complicated non-linear system having expansive allocations. The adaptive learning algorithm is formed in such a way that the learning rate is as large as possible while maintaining the stability of the learning process. This simplifies the learning process in terms of computation time, which is of special importance in real-time implementation.